Database sharing in a virtual private deployment

ABSTRACT

A network device communication system can configure network devices, such as a first database in a multi-tenant deployment and a second database in a private deployment, to send and receive sequence messages, such as replication data, over a channel comprising a plurality of private network nodes. The first database can create a link specifying the data share and the second database. The second database selects the link and a secure area in the private deployment is created into which data is replicated and shared with further accounts in a computationally secure and efficient manner.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of earlier filing date and right ofpriority to U.S. Provisional Patent Application Ser. No. 63/287,885,filed on Dec. 9, 2021, entitled “DATABASE SHARING IN A VIRTUAL PRIVATEDEPLOYMENT” (Attorney Docket No. 5397.154PRV), the contents of which arehereby incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure generally relates to special-purpose machinesthat manage database data and improvements to such variants, and to thetechnologies by which such special-purpose machines become improvedcompared to other special-purpose machines for transmitting databasedata between databases connected by a network.

BACKGROUND

Databases are used for data storage and access in computingapplications. A goal of database storage is to provide enormous sums ofinformation in an organized manner so that data can be accessed,managed, and updated. In a database, data can be organized into rows,columns, and tables. Different database storage systems can be used forstoring distinct types of content, such as bibliographic, full text,numeric, and/or image content. Further, in computing, different databasesystems can be classified according to the organization approach of thedatabase. There are many diverse types of databases, includingrelational databases, distributed databases, cloud databases, andothers.

BRIEF DESCRIPTION OF THE DRAWINGS

Various ones of the appended drawings merely illustrate exampleembodiments of the present disclosure and should not be considered aslimiting its scope.

FIG. 1 illustrates an example computing environment in which a clouddata platform can implement streams on shared data storage devices,according to some example embodiments.

FIG. 2 is a block diagram illustrating components of a compute servicemanager, according to some example embodiments.

FIG. 3 is a block diagram illustrating components of an executionplatform, according to some example embodiments.

FIG. 4 is a block diagram illustrating a database architecture fortransmission of database data over a channel, according to some exampleembodiments.

FIG. 5 is a block diagram illustrating a share data architecture,according to some example embodiments.

FIG. 6 is a block diagram depicting a secure share data replication,according to example embodiments.

FIG. 7 is an interface diagram illustrating a share creation userinterface for securely sharing data to a virtual private deployment of adistributed database system, according to some example embodiments.

FIG. 8 is a flow diagram illustrating operations of a method for sharingdata into a virtual private deployment, according to some exampleembodiments.

FIG. 9 illustrates a diagrammatic representation of a machine in theform of a computer system within which a set of instructions can beexecuted for causing the machine to perform any one or more of themethodologies discussed herein, in accordance with some embodiments ofthe present disclosure.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments of the inventive subject matter. It will be evident,however, to those skilled in the art, that embodiments of the inventivesubject matter can be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

In some instances, it can be beneficial to replicate database data inmultiple locations or on multiple storage devices. Replicating data cansafeguard against system failures that may render data inaccessible,cause the data to be lost or cause the data to be permanentlyunreadable. While replication between different databases increases thesafety of the data, the data should be securely transmitted between thereplication databases. Some database systems use encryption keys toauthenticate one another and to encrypt data sent between the differentdatabase systems. For example, a database instance in one datacenter canuse an encryption key to authenticate and receive communications fromanother database instance in another datacenter that is located at adifferent geographic location. While replication of database data andencryption keys increase the security of the data, implementing suchapproaches in different networked database systems, such as clouddatabases, can be difficult to perform in a manner that iscomputationally efficient and secure.

As discussed, it can be difficult to securely manage database trafficsent and received between database systems. Prior relevant technologiessimply enabled provider users to share data to a consumer user directlyto the consumer's multi-tenant account. The consumer would thenmaterialize the shared data in their multi-tenant account and replicatethe shared data to a virtual private cloud (VPC) deployment account.However, this created a technical problem for VPC deployment userswithout multi-tenant accounts and required an intermediate step to loadstructured data from a third-party external source into a databaseemploying extraction-transform-load (ETL) process.

An example cloud data platform includes a VPC deployment that uses clouddata storage devices and cloud compute resources dedicated to thatdeployment. Different deployments can be linked, and channels can be setup to send and receive data between the deployments. The VPC deploymentis a virtualized environment that runs on the cloud data system hardwareinstances, which are physically isolated from other users of the system.The VPC deployment is an on-demand configurable pool of shared resourcesallocated within a public cloud environment and provides a level ofisolation between different users (e.g., different organizations) usingthe VPC resources.

Example embodiments disclosed herein provide technical solutions tomanage database traffic securely between isolated database systems byenabling VPC deployment users to identify and authorize a data providerto share data directly to the VPC deployment. Once the VPC deploymentaccount has been authorized, the provider can create a listing andtarget the specific VPC deployment account. Such improvements asdescribed throughout provide a secure shared area where data isreplicated automatically when a consumer-user requests the data.

For example, a first VPC deployment, deployment_A, can be a deployment(e.g., a database management system (DBMS) running within an Amazon WebServices® (AWS) Virtual Private Cloud (VPC)) at a first region, such asSan Francisco, and a second VPC deployment, deployment_B, can be anotherdeployment (e.g., another DBMS in a different AWS VPC) at a secondregion, such as New York City. Deployment_A and deployment_B can createa link over which a stream of data, such as replication traffic, is sentbetween the two deployments. For example, replication traffic of aprimary database in deployment_A can be replicated to a secondarydatabase located in deployment_B.

While it may be possible to replicate the traffic from deployment_A todeployment_B, it can still be difficult to ensure that the data takes acertain path or stays within a certain region while in transit betweenthe two deployments. For instance, a database administrator may requirethat none of its data in its databases ever be transferred over the openInternet. Further, to comply with data governance laws, the databaseadministrator may seek to configure their databases such that all datain the database network stays within a certain region. For example, thedatabase administrator may seek to ensure that all data transferredbetween deployment_A and deployment_B remain within a given country(e.g., USA) and additionally the data may never be transferred over theopen Internet (e.g., encrypted in TLS traffic over the Internet) whilein the given country.

Additionally, many VPCs are not configured for replication between thedifferent VPCs and may charge egress export fees (e.g., egress fees)even though the traffic is being replicated to another deployment of thesame VPC provider. Further difficulty arises when sending data betweendifferent types of database deployments securely. For example, ifdeployment_A is a VPC from a first provider (e.g., AWS VPC) anddeployment_B is a VPC from second different provider (e.g., GooglePrivate Cloud (GPC)), the different providers may have different andpotentially incongruent security mechanisms. For instance, deployment_Bmay implement a hardware security module (HSM) that does not enableimporting or exporting of encryption keys, thereby greatly increasingthe difficulty and practicality of transferring data between thedeployments. Additionally, even when the different deployments havecongruent security mechanisms (e.g., each deployment has an HSM thatenables import/export of keys), managing the keys as the number ofreplicated databases increases to enterprise levels (e.g., hundreds ofthousands of database customers at the different deployments, where eachreplicates data to other database in other deployments) is exceedinglydifficult to implement in a secure manner that scales with networkgrowth.

To address these issues, a replication manager and channel manager canbe implemented in a deployment to encrypt the traffic in an approachthat is agnostic to various configurations of HSMs and VPCs, and furtherto transfer the traffic between deployments using nodes of a privatenetwork that are external to the deployments. For example, the privatenetwork can be a virtual private network (VPN) that implements VPN nodes(e.g., AT&T® NetBond® nodes, a VPN server/node at a first location andanother VPN server/node at a second location) to transfer traffic withinthe virtual private network. When one or more databases in deployment_Asend data to another database in deployment_B (e.g., replicationtraffic) the channel manager can implement a cloud connection (e.g.,hosted connections provided by the given VPC provider such as AWS DirectConnect®, or a physical connection such as Ethernet port) to send datafrom deployment_A to a node of the virtual private network.

Each of the nodes of the virtual private network can be set up andpositioned within a given region (e.g., in a country, oravoiding/excluding a specified country), thereby ensuring the data isnot transferred outside the region and not exposed or otherwisetransferred over the open Internet. The traffic continues over the VPNnodes to the destination database in deployment_B. In some exampleembodiments, the VPN node nearest deployment_B then imports the trafficinto the destination database using a cloud connection provided bydeployment_B (e.g., hosted connection of the cloud, such as AWS DirectConnect; a direct port connection such as Azure Express Route®; aphysical Ethernet cord connecting the VPN node to hardware ofdeployment_B, etc.).

Additionally, and in accordance with some example embodiments, thetraffic is encrypted using internal message keys to efficiently transferthe traffic between the databases at different deployments. In someexample embodiments, a replication manager can generate the messages andkeys at the database application level, without requiring changes to agiven VPC, HSM, or VPN node transfer network. For example, in someexample embodiments, the traffic is sent in a sequence of messages usinga pre-configured key encryption structure. In some example embodiments,in each message, the data is encrypted by a symmetric key (e.g., dataencryption key (DEK) unique to that message). The data encryption keyfor the given message can be further encrypted by a wrapping replicationkey (WRK), which can be another symmetric key generated by the sendingdeployment (e.g., periodically generated by an HSM in deployment_A). Insome example embodiments, the WRK is then encrypted by a key from akeypair, such as the public key of the destination deployment. In someexample embodiments, the encrypted WRK to access a DEK in a givenmessage is also stored in the given message. In other exampleembodiments, the WRKs are staggered between messages such that a givenmessage's DEK is encrypted using a previously sent WRK (e.g., a WRK sentin a previously received message). Further, in some example embodiments,the WRKs are rotated based on time expiration periods or randomly toincrease security of the data. In this way, the replication manager andchannel manager of the database systems (e.g., database applicationsrunning on VPNs) can efficiently and securely transmit data betweendifferent clouds at the applications level over specific paths evenwhere the cloud systems are incongruent or cannot be customized.

FIG. 1 illustrates an example computing environment 100 that includes adatabase system in the example form of a cloud data platform 102, inaccordance with some embodiments of the present disclosure. To avoidobscuring the inventive subject matter with unnecessary detail, variousfunctional components that are not germane to conveying an understandingof the inventive subject matter have been omitted from FIG. 1 . However,a skilled artisan will readily recognize that various additionalfunctional components may be included as part of the computingenvironment 100 to facilitate additional functionality that is notspecifically described herein. In other embodiments, the computingenvironment may comprise another type of network-based database systemor a cloud data platform.

As shown, the computing environment 100 comprises the cloud dataplatform 102 in communication with a cloud storage platform 104 (e.g.,AWS®, Microsoft Azure Blob Storage®, or Google Cloud Storage). The clouddata platform 102 is a network-based system used for reporting andanalysis of integrated data from one or more disparate sources includingone or more storage locations within the cloud storage platform 104. Thecloud data platform 102 can be a network- based data platform ornetwork-based data system. The cloud storage platform 104 comprises aplurality of computing machines and provides on-demand computer systemresources such as data storage and computing power to the cloud dataplatform 102.

The cloud data platform 102 comprises a compute service manager 108, anexecution platform 110, and one or more metadata databases 112. Thecloud data platform 102 hosts and provides data reporting and analysisservices to multiple client accounts.

The compute service manager 108 coordinates and manages operations ofthe cloud data platform 102. The compute service manager 108 alsoperforms query optimization and compilation as well as managing clustersof computing services that provide compute resources (also referred toas “virtual warehouses”). The compute service manager 108 can supportany number of client accounts such as end users providing data storageand retrieval requests, system administrators managing the systems andmethods described herein, and other components/devices that interactwith compute service manager 108.

The compute service manager 108 is also in communication with a clientdevice 114. The client device 114 corresponds to a user of one of themultiple client accounts supported by the cloud data platform 102. Auser may utilize the client device 114 to submit data storage,retrieval, and analysis requests to the compute service manager 108.

The compute service manager 108 is also coupled to one or more metadatadatabases 112 that store metadata pertaining to various functions andaspects associated with the cloud data platform 102 and its users. Forexample, a metadata database 112 may include a summary of data stored inremote data storage systems as well as data available from a localcache. Additionally, a metadata database 112 may include informationregarding how data is organized in remote data storage systems (e.g.,the cloud storage platform 104) and the local caches. Information storedby a metadata database 112 allows systems and services to determinewhether a piece of data needs to be accessed without loading oraccessing the actual data from a storage device.

The compute service manager 108 is further coupled to the executionplatform 110, which provides multiple computing resources that executevarious data storage and data retrieval tasks. The execution platform110 is coupled to cloud storage platform 104. The cloud storage platform104 comprises multiple data storage devices 120-1 to 120-N. In someembodiments, the data storage devices 120-1 to 120-N are cloud-basedstorage devices located in one or more geographic locations. Forexample, the data storage devices 120-1 to 120-N can be part of a publiccloud infrastructure or a private cloud infrastructure. The data storagedevices 120-1 to 120-N may be hard disk drives (HDDs), solid statedrives (SSDs), storage clusters, Amazon S3™ storage systems, or anyother data storage technology. Additionally, the cloud storage platform104 may include distributed file systems (such as Hadoop DistributedFile Systems (HDFS)), object storage systems, and the like.

Since a shared data object or data set may include confidential or othertypes of sensitive data, securing the data set is a significantconsideration for participating client devices (e.g., client devicesassociated with data providers or data consumers). Existing third-partysecure sharing tools are time-consuming and cumbersome. A securedocument sharing manager 109 may be operatively connected to the computeservice manager 108 within the cloud data platform 102. The computeservice manager 108 may include a secure document sharing manager 109.The secure document sharing manager 109 comprises suitable circuitry,logic, interfaces, and/or code and is configured to performfunctionalities discussed herein in connection with secure documentsharing, also referred to herein as secure data sharing or secure objectsharing, within the computing environment 100. For example, the securedocument sharing manager 109 is configured to detect queries for shareddata and invoke security functions configured in the execution platform110.

In some embodiments, the secure document sharing manager 109 maydetermine whether or not to invoke (or trigger) secure document sharingfunctions based on analysis of metadata associated with a data object ordata file (e.g., data file responsive to a query) or multiple data filesof a data producer stored in an external or internal stage. For example,certain types of data files (e.g., unstructured data files containing akeyword or other metadata) can be selected for processing using thedisclosed secure document sharing techniques based on metadata analysis.

The execution platform 110 comprises a plurality of compute nodes. A setof processes on a compute node executes a query plan compiled by thecompute service manager 108. The set of processes can include: a firstprocess to execute the query plan; a second process to monitor anddelete cache files using a least recently used (LRU) policy andimplement an out of memory (OOM) error mitigation process; a thirdprocess that extracts health information from process logs and status tosend back to the compute service manager 108; a fourth process toestablish communication with the compute service manager 108 after asystem boot; and a fifth process to handle all communication with acompute cluster for a given job provided by the compute service manager108 and to communicate information back to the compute service manager108 and other compute nodes of the execution platform 110.

In some embodiments, communication links between elements of thecomputing environment 100 are implemented via one or more datacommunication networks. These data communication networks may utilizeany communication protocol and any type of communication medium. In someembodiments, the data communication networks are a combination of two ormore data communication networks (or sub-Networks) coupled to oneanother. In alternate embodiments, these communication links areimplemented using any type of communication medium and any communicationprotocol.

The compute service manager 108, metadata database(s) 112, executionplatform 110, and cloud storage platform 104 are shown in FIG. 1 asindividual discrete components. However, each of the compute servicemanager 108, metadata database(s) 112, execution platform 110, and cloudstorage platform 104 can be implemented as a distributed system (e.g.,distributed across multiple systems/platforms at multiple geographiclocations). Additionally, each of the compute service manager 108,metadata database(s) 112, execution platform 110, and cloud storageplatform 104 can be scaled up or down (independently of one another)depending on changes to the requests received and the changing needs ofthe cloud data platform 102. Thus, in the described embodiments, thecloud data platform 102 is dynamic and supports regular changes to meetthe current data processing needs.

During typical operation, the cloud data platform 102 processes multiplejobs determined by the compute service manager 108. These jobs arescheduled and managed by the compute service manager 108 to determinewhen and how to execute the job. For example, the compute servicemanager 108 may divide the job into multiple discrete tasks and maydetermine what data is needed to execute each of the multiple discretetasks. The compute service manager 108 may assign each of the multiplediscrete tasks to one or more nodes of the execution platform 110 toprocess the task. The compute service manager 108 may determine whatdata is needed to process a task and further determine which nodeswithin the execution platform 110 are best suited to process the task.Some nodes may have already cached the data needed to process the taskand, therefore, be a suitable candidate for processing the task.Metadata stored in a metadata database 112 assists the compute servicemanager 108 in determining which nodes in the execution platform 110have already cached at least a portion of the data needed to process thetask. One or more nodes in the execution platform 110 process the taskusing data cached by the nodes and, if necessary, data retrieved fromthe cloud storage platform 104. It is desirable to retrieve as much dataas possible from caches within the execution platform 110 because theretrieval speed is typically much faster than retrieving data from thecloud storage platform 104.

As shown in FIG. 1 , the computing environment 100 separates theexecution platform 110 from the cloud storage platform 104. In thisarrangement, the processing resources and cache resources in theexecution platform 110 operate independently of the data storage devices120-1 to 120-N in the cloud storage platform 104. Thus, the computingresources and cache resources are not restricted to specific datastorage devices 120-1 to 120-N. Instead, all computing resources and allcache resources may retrieve data from, and store data to, any of thedata storage resources in the cloud storage platform 104.

FIG. 2 is a block diagram 200 illustrating components of the computeservice manager 108, in accordance with some embodiments of the presentdisclosure. As shown in FIG. 2 , the compute service manager 108includes an access manager 202 and a credential management system 204coupled to access data storage device 206, which is an example of themetadata database(s) 112. Access manager 202 handles authentication andauthorization tasks for the systems described herein. The credentialmanagement system 204 facilitates use of remote stored credentials toaccess external resources such as data resources in a remote storagedevice. As used herein, the remote storage devices may also be referredto as “persistent storage devices” or “shared storage devices.” Forexample, the credential management system 204 may create and maintainremote credential store definitions and credential objects (e.g., in theaccess metadata database 206). A remote credential store definitionidentifies a remote credential store and includes access information toaccess security credentials from the remote credential store. Acredential object identifies one or more security credentials usingnon-sensitive information (e.g., text strings) that are to be retrievedfrom a remote credential store for use in accessing an externalresource. When a request invoking an external resource is received atrun time, the credential management system 204 and access manager 202use information stored in the access metadata database 206 (e.g., acredential object and a credential store definition) to retrievesecurity credentials used to access the external resource from a remotecredential store.

A request processing service 208 manages received data storage requestsand data retrieval requests (e.g., jobs to be performed on databasedata). For example, the request processing service 208 may determine thedata to process a received query (e.g., a data storage request or dataretrieval request). The data can be stored in a cache within theexecution platform 110 or in a data storage device in cloud storageplatform 104.

A management console service 210 supports access to various systems andprocesses by administrators and other system managers. Additionally, themanagement console service 210 may receive a request to execute a joband monitor the workload on the system.

The compute service manager 108 also includes a job compiler 212, a joboptimizer 214, and a job executor 216. The job compiler 212 parses a jobinto multiple discrete tasks and generates the execution code for eachof the multiple discrete tasks. The job optimizer 214 determines thebest method to execute the multiple discrete tasks based on the datathat needs to be processed. The job optimizer 214 also handles variousdata pruning operations and other data optimization techniques toimprove the speed and efficiency of executing the job. The job executor216 executes the execution code for jobs received from a queue ordetermined by the compute service manager 108.

A job scheduler and coordinator 218 sends received jobs to theappropriate services or systems for compilation, optimization, anddispatch to the execution platform 110. For example, jobs can beprioritized and then processed in that prioritized order. In anembodiment, the job scheduler and coordinator 218 determines a priorityfor internal jobs that are scheduled by the compute service manager 108with other “outside” jobs such as user queries that can be scheduled byother systems in the database but may utilize the same processingresources in the execution platform 110. In some embodiments, the jobscheduler and coordinator 218 identifies or assigns particular nodes inthe execution platform 110 to process particular tasks. A virtualwarehouse manager 220 manages the operation of multiple virtualwarehouses implemented in the execution platform 110. For example, thevirtual warehouse manager 220 may generate query plans for executingreceived queries.

A secure share system 230 is configured to share data from amulti-tenant deployment to a virtual private deployment on the clouddata platform 102 in a secure and efficient manner, as discussed infurther detail below. The secure document sharing manager 109 may beoperatively connected to secure share system 230.

Example embodiments of the secure share system 230 provide for sharing a“shared data object,” “database object,” or “share object” between aprovider account and a consumer account in a cloud data system, such asthe cloud data platform 102. The secure share system enables sharingbetween a first deployment, such as a provider, and a second deployment,such as a consumer. it should be appreciated that the terms “provider”and “consumer” are illustrative only and may alternatively he referredto as a first account and a second account, as a sharer account and atarget account, as a provider and a receiver, and so forth

The secure document sharing manager 109, alone or in combination withthe secure share system 230, is enabled to manage sharing of documents,such as a share object, between the one or more accounts in the one ormore deployments. The share object or shared data in one implementationmay include procedural logic that is defined by a user of a provideraccount (in one implementation, by a user of the sharer account). Theshare object may be supported in scalar and table-valued user-definedfunctions (UDFs) and may be defined by any suitable language. Theprocedural logic a the share object may be used by one or more otheraccounts without permitting the one or more other accounts to view theunderlying code defining the procedural logic. The share object orshared data may further include database data such as data stored in atable of the database. The share object can include metadata aboutdatabase data such as minimum/maximum values for a table ormicro-partition of a database, underlying structural or architecturaldetails of the database data, and so forth.

The secure document sharing manager 109 can further be enabled to managethe types of data in the share object. For example, the share object caninclude a listing of all other accounts that can receive cross-accountaccess rights to elements of the share object. The listing may indicate,for example, that a second account may use procedural logic of the shareobject without seeing any underlying code defining the procedural logic.The listing may further indicate, for example, that a third account mayuse database data of one or more tables without seeing any structuralinformation or metadata about the database data. The listing mayindicate any combination of usage privileges for elements of the shareobject, including whether secondary accounts may see metadata orstructural information for database data or procedural logic.

Additionally, the compute service manager 108 includes a configurationand metadata manager 222, which manages the information related to thedata stored in the remote data storage devices and in the local buffers(e.g., the buffers in execution platform 110). The configuration andmetadata manager 222 uses metadata to determine which data files need tobe accessed to retrieve data for processing a particular task or job. Amonitor and workload analyzer 224 oversees processes performed by thecompute service manager 108 and manages the distribution of tasks (e.g.,workload) across the virtual warehouses and execution nodes in theexecution platform 110. The monitor and workload analyzer 224 alsoredistributes tasks, as needed, based on changing workloads throughoutthe cloud data platform 102 and may further redistribute tasks based ona user (e.g., “external”) query workload that may also be processed bythe execution platform 110. The configuration and metadata manager 222and the monitor and workload analyzer 224 are coupled to a data storagedevice 226. Data storage device 226 in FIG. 2 represents any datastorage device within the cloud data platform 102. For example, datastorage device 226 may represent buffers in execution platform 110,storage devices in cloud storage platform 104, or any other storagedevice.

As described in embodiments herein, the compute service manager 108validates all communication from an execution platform (e.g., theexecution platform 110) to validate that the content and context of thatcommunication are consistent with the task(s) known to be assigned tothe execution platform. For example, an instance of the executionplatform executing a query A should not be allowed to request access todata-source D (e.g., data storage device 226) that is not relevant toquery A. Similarly, a given execution node (e.g., execution node 302-1)may need to communicate with another execution node (e.g., executionnode 302-2), and should be disallowed from communicating with a thirdexecution node (e.g., execution node 312-1) and any such illicitcommunication can be recorded (e.g., in a log or other location). Also,the information stored on a given execution node is restricted to datarelevant to the current query and any other data is unusable, renderedso by destruction or encryption where the key is unavailable.

FIG. 3 is a block diagram 300 illustrating components of the executionplatform 110, in accordance with some embodiments of the presentdisclosure. As shown in FIG. 3 , the execution platform 110 includesmultiple virtual warehouses, including virtual warehouse 1, virtualwarehouse 2, and virtual warehouse N. Each virtual warehouse includesmultiple execution nodes that each include a data cache and a processor.The virtual warehouses can execute multiple tasks in parallel by usingthe multiple execution nodes. As discussed herein, the executionplatform 110 can add new virtual warehouses and drop existing virtualwarehouses in real-time based on the current processing needs of thesystems and users. This flexibility allows the execution platform 110 toquickly deploy large amounts of computing resources when needed withoutbeing forced to continue paying for those computing resources when theyare no longer needed. All virtual warehouses can access data from anydata storage device (e.g., any storage device in cloud storage platform104).

Although each virtual warehouse shown in FIG. 3 includes three executionnodes, a particular virtual warehouse may include any number ofexecution nodes. Further, the number of execution nodes in a virtualwarehouse is dynamic, such that new execution nodes are created whenadditional demand is present, and existing execution nodes are deletedwhen they are no longer useful.

Each virtual warehouse is capable of accessing any of the data storagedevices 120-1 to 120-N shown in FIG. 1 . Thus, the virtual warehousesare not necessarily assigned to a specific data storage device 120-1 to120-N and, instead, can access data from any of the data storage devices120-1 to 120-N within the cloud storage platform 104. Similarly, each ofthe execution nodes shown in FIG. 3 can access data from any of the datastorage devices 120-1 to 120-N. In some embodiments, a particularvirtual warehouse or a particular execution node can be temporarilyassigned to a specific data storage device, but the virtual warehouse orexecution node may later access data from any other data storage device.

In the example of FIG. 3 , virtual warehouse 1 includes three executionnodes 302-1, 302-2, and 302-N. Execution node 302-1 includes a cache304-1 and a processor 306-1. Execution node 302-2 includes a cache 304-2and a processor 306-2. Execution node 302-N includes a cache 304-N and aprocessor 306-N. Each execution node 302-1, 302-2, and 302-N isassociated with processing one or more data storage and/or dataretrieval tasks. For example, a virtual warehouse may handle datastorage and data retrieval tasks associated with an internal service,such as a clustering service, a materialized view refresh service, afile compaction service, a storage procedure service, or a file upgradeservice. In other implementations, a particular virtual warehouse mayhandle data storage and data retrieval tasks associated with aparticular data storage system or a particular category of data.

Similar to virtual warehouse 1 discussed above, virtual warehouse 2includes three execution nodes 312-1, 312-2, and 312-N. Execution node312-1 includes a cache 314-1 and a processor 316-1. Execution node 312-2includes a cache 314-2 and a processor 316-2. Execution node 312-Nincludes a cache 314-N and a processor 316-N. Additionally, virtualwarehouse N includes three execution nodes 322-1, 322-2, and 322-N.Execution node 322-1 includes a cache 324-1 and a processor 326-1.Execution node 322-2 includes a cache 324-2 and a processor 326-2.Execution node 322-N includes a cache 324-N and a processor 326-N.

In some embodiments, the execution nodes shown in FIG. 3 are statelesswith respect to the data being cached by the execution nodes. Forexample, these execution nodes do not store or otherwise maintain stateinformation about the execution node, or the data being cached by aparticular execution node. Thus, in the event of an execution nodefailure, the failed node can be transparently replaced by another node.Since there is no state information associated with the failed executionnode, the new (replacement) execution node can easily replace the failednode without concern for recreating a particular state.

Although the execution nodes shown in FIG. 3 each includes one datacache and one processor, alternate embodiments may include executionnodes containing any number of processors and any number of caches.Additionally, the caches may vary in size among the different executionnodes. The caches shown in FIG. 3 store, in the local execution node,data that was retrieved from one or more data storage devices in cloudstorage platform 104. Thus, the caches reduce or eliminate thebottleneck problems occurring in platforms that consistently retrievedata from remote storage systems. Instead of repeatedly accessing datafrom the remote storage devices, the systems and methods describedherein access data from the caches in the execution nodes, which issignificantly faster and avoids the bottleneck problem discussed above.In some embodiments, the caches are implemented using high-speed memorydevices that provide fast access to the cached data. Each cache canstore data from any of the storage devices in the cloud storage platform104.

Further, the cache resources and computing resources may vary betweendifferent execution nodes. For example, one execution node may containsignificant computing resources and minimal cache resources, making theexecution node useful for tasks that require significant computingresources. Another execution node may contain significant cacheresources and minimal computing resources, making this execution nodeuseful for tasks that require caching of large amounts of data. Yetanother execution node may contain cache resources providing fasterinput-output operations, useful for tasks that require fast scanning oflarge amounts of data. In some embodiments, the cache resources andcomputing resources associated with a particular execution node aredetermined when the execution node is created, based on the expectedtasks to be performed by the execution node.

Additionally, the cache resources and computing resources associatedwith a particular execution node may change over time based on changingtasks performed by the execution node. For example, an execution nodemay be assigned more processing resources if the tasks performed by theexecution node become more processor intensive. Similarly, an executionnode may be assigned more cache resources if the tasks performed by theexecution node require a larger cache capacity.

Although virtual warehouses 1, 2, and N are associated with the sameexecution platform 110, the virtual warehouses can be implemented usingmultiple computing systems at multiple geographic locations. Forexample, virtual warehouse 1 can be implemented by a computing system ata first geographic location, while virtual warehouses 2 and N areimplemented by another computing system at a second geographic location.In some embodiments, these different computing systems are cloud-basedcomputing systems maintained by one or more different entities.

Additionally, each virtual warehouse is shown in FIG. 3 as havingmultiple execution nodes. The multiple execution nodes associated witheach virtual warehouse can be implemented using multiple computingsystems at multiple geographic locations. For example, an instance ofvirtual warehouse 1 implements execution nodes 302-1 and 302-2 on onecomputing platform at a geographic location and implements executionnode 302-N at a different computing platform at another geographiclocation. Selecting particular computing systems to implement anexecution node may depend on various factors, such as the level ofresources needed for a particular execution node (e.g., processingresource requirements and cache requirements), the resources availableat particular computing systems, communication capabilities of networkswithin a geographic location or between geographic locations, and whichcomputing systems are already implementing other execution nodes in thevirtual warehouse.

Execution platform 110 is also fault tolerant. For example, if onevirtual warehouse fails, that virtual warehouse is quickly replaced witha different virtual warehouse at a different geographic location.

A particular execution platform 110 may include any number of virtualwarehouses. Additionally, the number of virtual warehouses in aparticular execution platform is dynamic, such that new virtualwarehouses are created when additional processing and/or cachingresources are needed. Similarly, existing virtual warehouses can bedeleted when the resources associated with the virtual warehouse are nolonger useful.

In some embodiments, the virtual warehouses may operate on the same datain cloud storage platform 104, but each virtual warehouse has its ownexecution nodes with independent processing and caching resources. Thisconfiguration allows requests on different virtual warehouses to beprocessed independently and with no interference between the requests.This independent processing, combined with the ability to dynamicallyadd and remove virtual warehouses, supports the addition of newprocessing capacity for new users without impacting the performance.

FIG. 4 shows an example database architecture 400 for transmission ofdatabase data over a channel (e.g., private channel), according to someexample embodiments. As discussed above, an HSM is a hardware securitymodule, which is a physical computing device that safeguards and managesdigital keys for strong authentication. Example HSMs can be implementedas a plug-in card or server rack module that attaches directly to acomputer or network service running within the deployment's cloudexecution instances (e.g., within the VPN of the cloud platform, such asAWS). In some example embodiments, a given deployment's HSM is providedby the cloud provider as a network service, along with the providedexecution units (e.g., Amazon S3, Google Cloud, Microsoft Azure eachoffer HSM services for their cloud compute units, e.g., virtualmachines).

In some example embodiments, the encryption keys are generated andmanaged by the HSMs in each deployment. As discussed above, if twodeployments are being connected (e.g., a mesh of deployments), this canmake use of exporting encryption keys (e.g., symmetric key, privatekeys, public key, key pairs) out of one deployment's HSM and importingthe key data into another deployment's HSM (e.g., a new deployment thatis being added to the mesh). For example, to safeguard data, an existingdeployment is replicated resulting in the creation of a new deployment,the data from the existing deployment is copied or otherwise replicatedover to the new deployment, the key is exported by the existingdeployment's HSM, and the key is imported by the new deployment's HSM.After creation and exporting/importing of the key, the new deploymentcan function as a secondary or replication deployment that stores datareplicated from the existing deployment, which then functions as a“primary” or source deployment. While HSMs provide secure encryptionfunctions, HSM processing does not scale well and can increase theprocessing overhead as more deployments are added to a given networkedsystem. Thus, there is an existing demand for using non-HSM operationswhere possible, so long as the non-HSM processing can be performedsecurely.

Furthermore, not all HSMs provide key importing or exporting functions,which inhibits replication of deployments using such systems. Oneapproach to handling HSM scaling issues involves creating a public keydocument that stores each deployment's public key, where new deploymentsadd their public key to the public key document and encrypt outboundmessages with the target deployment's public key (which is thendecryptable by the target deployment via its private key). However, oneissue with this approach is that it can be difficult to manage thepublic key document in a secure manner, as the number of deploymentsscale to enterprise levels.

Additionally, even if a given deployment knows the target deployment'spublic key, which does not ensure that the target deployment is who itsays it is. That is, for example, the target deployment can be acompromised or otherwise malicious deployment that is seeking tointercept data by proffering the compromised or malicious deployment'spublic key to other legitimate deployments in the mesh. Additionally, itis impractical to perform key rotation using the public key document(where key rotation is when each public key is replaced with a newpublic key), at least in part because each deployment would rotate theirkeys at the same time, which is difficult to do in practice and can beprone to errors.

To solve these issues, a replication manager can implement asymmetrickeys and one or more symmetric keys to transmit data between databases,such as a source deployment (e.g., a primary database application in aVPN) and a target deployment (e.g., one or more secondary or replicateddatabases in another VPN cloud). In some example embodiments, eachdeployment generates a replication asymmetric keypair (RAK) to send andreceive encrypted data, and an authentication asymmetric keypair (AAK)that is used to authenticate the given deployment. In some exampleembodiments, each deployment further generates a symmetric key toencrypt/decrypt each data file sent (e.g., data encryption key (DEK)),and a symmetric wrapping replication key (WRK) which wraps the DEKs,where the WRKs can be staggered across messages and constantly changedto further secure the sent data. The replication manager can use thesekeys in an authentication process and messaging protocol to securelysend and receive data between the deployments without reliance onimporting/exporting of keys from the HSMs.

Generally, an example asymmetric keypair includes PKI (Public KeyInfrastructure) keys comprising a private key and a corresponding publickey. The PKI keys are generated by the HSMs using cryptographicalgorithms based on mathematical problems to produce one-way functions.The keypair can be used to securely send data and also to authenticate agiven device. To securely send/receive data using an asymmetric keypair,the public key can be disseminated widely, and the private key is keptprivate to that deployment. In such a system, any sending deployment canencrypt a message using the target deployments' public key, but thatencrypted message can only be decrypted with that target deployment'sprivate key. To use a keypair as a signature or authenticationmechanism, a signing device uses the private key to “sign” a given dataitem, and other devices that have access to the public key canauthenticate that the signature on the data item is authentic becauseonly the signing device has the private key, and in such systems forgingthe signature is currently mathematically impractical.

Generally, a symmetric key is a shared secret that is shared between thetransmitter and receiver, where the shared secret (e.g., the symmetrickey) is used to encrypt the message and also to decrypt the message. Anexample symmetric key scheme includes Advanced Encryption Standard (AES)256, which can be generated by the HSM; additional symmetric key schemesinclude Twofish, Blowfish, Serpent, DES, and others.

Returning to the example illustrated in FIG. 4 , deployment 405 anddeployment 430 are separate instances of computing environment 100 ofFIG. 1 with various components discussed in FIGS. 1-3 omitted forclarity. That is, for example, deployment 405 is a first instance ofcomputing environment 100 installed within a first VPC at a firstgeographic location (e.g., AWS virtual private cloud hosted in SanFrancisco), and deployment 430 is a second difference instance ofcomputing environment 100 installed and hosted within a second VPC at asecond geographic location (e.g., a different AWS virtual private cloudhosted from New York City). Although only two deployments are discussedhere as an example, it is appreciated that each location may implementmultiple deployments within the same VPC or other VPCs. For example, theVPC that is hosting deployment 405 may have other deployments eachrunning their own instances of computing environment 100. Further,although the deployments are discussed as being geographicallyseparated, it is appreciated that the deployments can be located withinthe same geographic region, albeit on different cloud systems (e.g.,deployment 405 is a west coast AWS VPN instance of computing environment100 and deployment 430 a Google Cloud instance of computing environment100) or different subnets of a single cloud site at the same geographiclocation (e.g., both deployments are on a west coast AWS virtual privatecloud but on different partitioned subnets).

The consumer region includes one or more accounts, where the one or moreaccounts are associated with one or more respective consumers of thedata provided by the provider associated with the provider database. Anaccount of the one or more accounts includes one or more links (e.g.,listings). A listing may include metadata describing the shared data. Alisting points to one or more databases, such as a consumer database andone or more shares that are associated with a database.

In the illustrated example, deployment 405 includes a replicationmanager 415 that manages authentication of the deployment with otherdeployments (e.g., deployment 430 and/or other deployments in a meshwith deployment 405 and deployment 430). The deployment 405 furthercomprises global services 420, which is a consolidated or representativesub-system including instances of 202, 204, 206, 208, 210, 212, and 214displayed in FIG. 2 . The deployment 405 further includes a databasesystem 425 (e.g., Foundation Database (FDB)), which is anotherrepresentative sub-system including instances of 216, 218, and 220. Thedeployment 405 further includes HSM 410, which, as discussed, is ahardware security module that can generate and manage encryption keysfor the deployment 405. Further, deployment_A includes channel manager433 that manages transmission of data to and from other deployments overa channel 470.

Deployment 430 is an example deployment of computing environment 100located at a second geographic location (e.g., New York City). Asillustrated, deployment 430 includes a replication manager 440 thatmanages authentication of the deployment with other deployments (e.g.,deployment 405 and/or other deployments in a mesh with deployment 405and deployment 430). The deployment 430 further comprises globalservices 445, which is a consolidated or representative sub-systemincluding instances of 202, 204, 206, 208, 210, 212, and 214 displayedin FIG. 2 . The deployment 430 further includes a DB 450 (e.g., FDB),which is another representative sub-system including instances of 216,218, and 220. Further, deployment 430 includes channel manager 477 thatmanages transmission of data to and from other deployments over thechannel 470 (e.g., via one or more hosted connection to a privatenetwork), according to some example embodiments.

The database architecture 400 further includes global deploymentsecurity system 455, according to some example embodiments. Asillustrated, the global deployment security system 455 includes a globalHSM 460 which generates an asymmetric keypair, including a global publickey and a global private key 461. The global public key is widelydistributed (e.g., to all deployments in the mesh) and can be used bythe deployments to check whether an item of data (e.g., a public key ofan unknown deployment) was actually signed by the global signing key ofglobal deployment security system 455 (e.g., using PKI signingoperations discussed above). In the following example, deployment 405 isthe primary database and seeks to send replication traffic to deployment430, though it is appreciated that in reverse processes, thearchitecture 400 can be implemented to send traffic from deployment 430to deployment 405.

In some example embodiments, to authenticate the deployment 405, theglobal deployment security system 455 signs the authentication publickey of the deployment 405 with the global signing key, therebyindicating to other deployments that the deployment 405 is who it saysit is (e.g., that is, an authenticated deployment and not a malicious orcompromised deployment).

In some example embodiments, to initiate channel 470, deployment 405sends deployment 430 the authentication public key of deployment 405,which has been signed by the global signing key of global deploymentsecurity system 455. In some example embodiments, the setupcommunications are sent over the VPN nodes, while in other embodimentsthe setup communications are transmitted to destination deployments overthe Internet (e.g., encrypted traffic), where the setup communicationscan include key or authentication data that is not replication data,according to some example embodiments.

Deployment 430 receives the key data, and if the key is not signed bythe global deployment security system 455, the deployment 430 rejectsfurther communications from the deployment 405. Assuming the receivedpublic key is signed by the global deployment security system 455, thedeployment 430 saves network address data (e.g., URLs) and other datadescribing deployment 405 (e.g., tasks/functions) for furthercommunications.

In some example embodiments, after channel 470 is established, thedeployment 405 can send encrypted data to deployment 430, such asreplication files from one or more databases of deployment 405 (e.g.,data storage devices 124 connected to the execution units of deployment405). The messages of channel 470 are transmitted by way of one or morenodes or networked servers of a virtual private network. In some exampleembodiments, to encrypt and decrypt the data sent over the channel 470,HSM 410 generates a replication asymmetric key pair for deployment 405,and HSM 435 generates a replication asymmetric key pair for deployment430, where the public keys from of each deployment can be widely spreadand used to encrypt data sent to the destination deployment. Forexample, deployment 405 can send a data file encrypted with the publickey of deployment 430, so that only deployment 430 can decrypt the file.Further, each data message may initially be encrypted using a dataencryption key (DEK) and further encrypted using a wrapping replicationkey (e.g., a symmetric key different than the DEK), which can beincluded in the files sent to the destination deployment, e.g.,deployment 430.

Although in the above examples, two different asymmetric key pairs weregenerated for deployment 405—one for authentication and one for thesending of database data—in some example embodiments a single asymmetrickeypair is used to both authenticate the deployment and send theencrypted data. For example, a keypair can be generated for deployment405 and the public key of the keypair can be signed by the globalprivate key from the global deployment security system 455. After thepublic key pair is signed, the deployment 405 can send the signed publickey to deployment 430 to both authenticate deployment 405 and to latersend traffic to deployment 405. That is, for example, deployment 430receives the signed public key and knows that it can trust deployment405 because the public key is a signed global private key, which onlyglobal deployment security system 455 has access to (e.g., as managed byglobal HSM 460). Further, the deployment 430 can use the signed publickey to encrypt and send data back to deployment 405, where it isguaranteed that only deployment 405 can decrypt the data as onlydeployment 405 has the corresponding private key. In this way, and inaccordance with some example embodiments, a single asymmetric keypair isused to both authenticate and send data to a given deployment.

FIG. 5 shows the secure share data architecture 500, according to someexample embodiments. The multi-tenant deployment 505 comprises aplurality of provider accounts that operate computational devices withinthe same deployment as co-tenants. In the example illustrated, themulti-tenant deployment 505 comprises a provider account 510, which hasa database 515 and a share object 520. A share can include grantmetadata describing access grants made to the consumer database for theone or more consumers of the consumer region. The share is an objectthat acts as a wrapper or a container around the database. The shareincludes multiple objects and can be shared with various users, whichgrants those users access to those objects. In various differentembodiments, only entities that have had a given share shared with themare able to see and access whatever one or more objects that areassociated by that given share.

In some example embodiments, the provider account 510 creates a link(e.g., a listing) to share data with a consumer account 545 that is in avirtual private deployment 525, which is deployment dedicated or managedonly by a single organization (e.g., banking organization) and no othertenants are hosted in the virtual private deployment 525, unlike themulti-tenant deployment 505.

The consumer account 545 can receive and click on the link created bythe provider account 510 to share data with the virtual privatedeployment 525. Upon the link being selected, the secure shared area 530is automatically created by the secure share system 230 in the virtualprivate deployment 525 (e.g., programmatically, without end-userinteraction). The secure shared area 530 operates as a database account,with restrictions, including no user facing interface (e.g., no loginaccess). Further in response to the link being selected, the database515 is replicated into the secure shared area 530 as database replica535, and the share object 520 is replicated into the secure shared area530 as the share object replica 540.

In the exemplary embodiment of FIG. 5 , the data in the secure sharedarea 530 is then shared with the consumer account 545 as data shareobjects, which the consumer account 545 can mount as a consumer mounteddatabase 550. Once the consumer mounted database 550 is created and hasaccess to the replicated share data, the consumer account 545 can thenperform database operations (e.g., queries) on the provider's datawithin the virtual private deployment 525 in a secure andcomputationally efficient manner. The consumer mounted database 550includes only the replicated data from the share replication from theprovider account 510.

For example, a user of a cloud data platform, such as the cloud dataplatform 102, may be a provider-user, such as provider account 510, thatcreates “shares” and makes the “shares” available to other users of thedata platform to consume. Data providers may share a database or aportion of a database with one or more other data platform users, bymaintaining or supporting grants to provide granular access control toselected objects in the database (e.g., access privileges are grantedfor one or more specific objects in a database). A provider-user maycreate a “share” 520 of a database, where the “share” 520 may be anobject that encapsulates information required to share a database withother users. For example, a share may consist of privileges that grantaccess to one or more databases, data tables, data views, functions,stored procedures, schema containing the objects to share, privilegesthat grant access to the specific objects in the one or more databases,and/or consumer accounts with which the one or more databases and itsobjects are shared.

The database shares may be configured or created by the provider-userand accessed or imported by a data consumer or consumer-user, such asthe consumer account 545, of the data platform. Once a database isshared with or created in a consumer-user's platform from the share, allthe shared objects are accessible to the consumer-user. A consumer-user,also referred to as a consumer, data consumer, or the like, may includea user that creates one or more databases from one or more shares madeavailable by a data provider. For example, a data consumer, once ashared database is connected, can access and/or query the objects in thedatabase. In some example embodiments, a user may be a consumer, aprovider, or both a consumer and a provider of shared data.Additionally, third-party users may exist that share data from only asingle provider.

FIG. 6 shows a block diagram 600 depicting the share of secure data froma provider account 510 to a consumer account 545, according to someexample embodiments. In the example of FIG. 6 , the provider deploymentmay be a multi-tenant deployment 505 that includes a provider account510. The provider deployment 505 is used to initiate a secure data sharewith the consumer account 545 that is in a virtual private deployment525 where the virtual private deployment 525 is dedicated or managedonly by a single organization (e.g., banking organization) and no othertenants or users are hosted in the virtual private deployment 525,unlike the multi-tenant deployment 505.

As the provider account 510 cannot access the virtual private deployment525 of the consumer directly, the provider account 510 cannot access thesecured share area (SSA) 530 directly through a step 601. For example,the provider account will not acquire or access the private deploymentvia log-in credentials. In order to facilitate the secure sharing ofdata from the provider account 510 to the consumer account 545, theconsumer account must acknowledge that the provider account is anauthorized account to share data to the secure shared area 530. Thisenables the consumer user to decide which provider organization ispermitted to share data from a public region, into the private region ofthe virtual private deployment. The provider organization can be enabledto view which virtual private deployment 525 with which they areauthorized to share data, as well as be enabled to share into thevirtual private deployment via a system stored process or systemfunction.

For security (e.g., in order for the consumer account to maintain dataseparation) the provider organization cannot access the virtual privatedeployment 525 for other purposes. For example, the providerorganization is not authorized to create an account in the virtualprivate deployment. The provider account can further be authorized andenabled to share the same or different data to more than one account inthe virtual private deployment 525. In some examples, the provideraccount 510 is further authorized to remove select accounts from thesecure shared area or delete the provider-account-supplied data from thesecure share area 530. In additional examples, a provider account canview and maintain usage analytics and other metadata related to thesecure share area 530.

Returning to the example embodiment of FIG. 6 , once the consumeraccount 545 recognizes the provider account as an authorized provider,the consumer account provides consumer account information to theprovider account. For example, the consumer account 545 can provide theconsumer's virtual private deployment account alias to the authorizedprovider account. Once the consumer account 545 authorizes the provideraccount 510, the authorized provider account can share a link (e.g.,private listing) 602 created by the provider with the consumer account.The provider account will be configured to publish private listings tospecific consumers, and only those specific consumers will be able todiscover and get data from the private listing. For example, theprovider account can complete a fulfillment setup 604 with the clouddata platform.

Once the private listing 602 is shared, the consumer account 545 canrequest data from the provider account directly to the consumer'svirtual private deployment. For example, the consumer account 545provides information to the cloud data platform 102 that the consumeraccount requests data from the authorized provider account 510. Uponsuch consumer account demand, the cloud data platform provides automaticlisting replication such that secure sharing will be automaticallyreplicated when the consumer account demands data from a private listingin the provider's region. Further, upon such consumer account demand fordata, the cloud data platform 102 automatically creates 606 a securedshared area 530. Once the secure shared area 530 is created, the clouddata platform 102 automatically replicates the data 608 requested by theconsumer account. Once the secure shared area is created, the cloud dataplatform can receive notification of completion, and share the securedata 612 with the consumer account 545 in the virtual privatedeployment. The secure shared area 530 updates automatically based onautomatic or manual audits performed on the shared data 614. Theautomatic or manual audits performed on the shared data may includedetecting modifications to the data, changes to the data, updates to thedata, deletions of the data, or the like. Further examples provide aconfirmation of successful replication of the shared data between theprovider account and the secure shared area, as well as the share of theshare replica between the secure shared area and the consumer-mounteddatabase of the consumer account. Confirmation of success may includenotifying the provider account of the share replication completion, aswell as other notifications actions.

FIG. 7 shows a private deployment share creation user interface 700 forsecurely sharing data to a virtual private deployment of the cloud dataplatform 102, in accordance with some example embodiments. An element705 is a field that can be implemented to specify which data product toshare to the virtual private deployment (e.g., database 515 and shareobject 520). An element 710 is a description field in which strings thatdescribe the data to be shared can be included. An element 715 is afield to specify which provider account is publishing the data forsharing into the virtual private deployment. An element 720 is a fieldin which multiple consumer accounts can be specified by network address(e.g., URL) or identifier that is unique to the different consumeraccounts on the cloud data platform 102. In some example embodiments,only the consumer accounts that are input into the element 720 willreceive notifications or otherwise be able to access the data to beshared from the multi-tenant deployment (e.g., from the provider account510). An element 725 is a text field that indicates the data isautomatically replicated once the receiver requester data from thislisting (e.g., the data is automatically shared to the secure sharedarea 530 is automatically created within the virtual private deployment525 in response to the link being selected by the consumer account 545).An element 730 is a field to specify how often to sync the data from theprovider account in the multi-tenant deployment to the secure sharedarea in the virtual private deployment. An element 735 is a publishedmoment that causes the secured shared area to be created after whichpoint consumer accounts receive notification and data is replicated andshared, as discussed above.

FIG. 8 shows a flow diagram of a method 800 for sharing data into avirtual private deployment, according to some example embodiments. Themethod 800 can be embodied in machine-readable instructions forexecution by one or more hardware components (e.g., one or moreprocessors) such that the operations of the method 800 can be performedby components of the cloud data platform 102. Accordingly, the method800 is described below, by way of example with reference to componentsof the cloud data platform 102. However, it shall be appreciated thatmethod 800 can be deployed on various other hardware configurations andis not intended to be limited to deployment within the cloud dataplatform 102.

Depending on the embodiment, an operation of the method 800 can berepeated in different ways or involve intervening operations not shown.Though the operations of the method 800 can be depicted and described ina certain order, the order in which the operations are performed mayvary among embodiments, including performing certain operations inparallel or performing sets of operations in separate processes.

At operation 805, the secure share system 230 generates a share link.For example, the provider account 510 implements the private deploymentshare creation user interface 700 to create a share link for the data tobe shared with the consumer account 545 in the virtual privatedeployment 525.

At operation 810, the secure share system 230 creates a secure sharedarea 530 in the virtual private deployment 525 (e.g., in response to thelink of operation 805 being selected by the consumer account 545). Atoperation 815, the provider data is replicated. For example, thedatabase 515 and the share object 520 are replicated from the provideraccount 510 to the secure shared area 530. At operation 820, the secureshare system 230 shares the replicated data. For example, the databasereplica 535 the share object replica 540 is shared within the virtualprivate deployment 525 into a consumer account 545. At operation 825,the consumer account 545 performs one or more database operations on theshared data (e.g., queries).

In additional examples embodiments of the method 800, the provideraccount is authorized by the consumer account to share more than oneshare object via the secure shared area 530. Additional secure sharedareas can be created in the virtual private deployment from the sameauthorized provider account or from additional authorized provideraccounts.

FIG. 9 illustrates a diagrammatic representation of a machine 900 in theform of a computer system within which a set of instructions can beexecuted for causing the machine 900 to perform any one or more of themethodologies discussed herein, according to an example embodiment.Specifically, FIG. 9 shows a diagrammatic representation of the machine900 in the example form of a computer system, within which instructions916 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 900 to perform any one ormore of the methodologies discussed herein can be executed. For example,the instructions 916 may cause the machine 900 to execute any one ormore operations of any one or more of the methods described herein. Asanother example, the instructions 916 may cause the machine 900 toimplement portions of the data flows described herein. In this way, theinstructions 916 transform a general, non-programmed machine into aparticular machine 900 (e.g., the compute service manager 108, theexecution platform 110, client device 114) that is specially configuredto carry out any one of the described and illustrated functions in themanner described herein.

In alternative embodiments, the machine 900 operates as a standalonedevice or can be coupled (e.g., networked) to other machines. In anetworked deployment, the machine 900 may operate in the capacity of aserver machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 900 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a smart phone, a mobiledevice, a network router, a network switch, a network bridge, or anymachine capable of executing the instructions 916, sequentially orotherwise, that specify actions to be taken by the machine 900. Further,while only a single machine 900 is illustrated, the term “machine” shallalso be taken to include a collection of machines 900 that individuallyor jointly execute the instructions 916 to perform any one or more ofthe methodologies discussed herein.

The machine 900 includes processors 910, memory 930, and input/output(I/O) components 950 configured to communicate with each other such asvia a bus 902. In an example embodiment, the processors 910 (e.g., acentral processing unit (CPU), a reduced instruction set computing(RISC) processor, a complex instruction set computing (CISC) processor,a graphics processing unit (GPU), a digital signal processor (DSP), anapplication-specific integrated circuit (ASIC), a radio-frequencyintegrated circuit (RFIC), another processor, or any suitablecombination thereof) may include, for example, a processor 912 and aprocessor 914 that may execute the instructions 916. The term“processor” is intended to include multi-core processors 910 that maycomprise two or more independent processors (sometimes referred to as“cores”) that may execute instructions 916 contemporaneously. AlthoughFIG. 9 shows multiple processors 910, the machine 900 may include asingle processor with a single core, a single processor with multiplecores (e.g., a multi-core processor), multiple processors with a singlecore, multiple processors with multiple cores, or any combinationthereof

The memory 930 may include a main memory 932, a static memory 934, and astorage unit 936, all accessible to the processors 910 such as via thebus 902. The main memory 932, the static memory 934, and the storageunit 936 comprising a machine storage medium 938 may store theinstructions 916 embodying any one or more of the methodologies orfunctions described herein. The instructions 916 may also reside,completely or partially, within the main memory 932, within the staticmemory 934, within the storage unit 936, within at least one of theprocessors 910 (e.g., within the processor's cache memory), or anysuitable combination thereof, during execution thereof by the machine900.

The I/O components 950 include components to receive input, provideoutput, produce output, transmit information, exchange information,capture measurements, and so on. The specific I/O components 950 thatare included in a particular machine 900 will depend on the type ofmachine. For example, portable machines such as mobile phones willlikely include a touch input device or other such input mechanisms,while a headless server machine will likely not include such a touchinput device. It will be appreciated that the I/O components 950 mayinclude many other components that are not shown in FIG. 9 . The I/Ocomponents 950 are grouped according to functionality merely forsimplifying the following discussion and the grouping is in no waylimiting. In various example embodiments, the I/O components 950 mayinclude output components 952 and input components 954. The outputcomponents 952 may include visual components (e.g., a display such as aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), other signal generators, and soforth. The input components 954 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point-based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or another pointinginstrument), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

Communication can be implemented using a wide variety of technologies.The I/O components 950 may include communication components 964 operableto couple the machine 900 to a network 981 via a coupling 983 or todevices 980 via a coupling 982. For example, the communicationcomponents 964 may include a network interface component or anothersuitable device to interface with the network 981. In further examples,the communication components 964 may include wired communicationcomponents, wireless communication components, cellular communicationcomponents, and other communication components to provide communicationvia other modalities. The devices 980 can be another machine or any of awide variety of peripheral devices (e.g., a peripheral device coupledvia a universal serial bus (USB)). For example, as noted above, themachine 900 may correspond to any one of the client devices 114, thecompute service manager 108, the execution platform 110, and the devices980 may include any other of these systems and devices.

The various memories (e.g., 930, 932, 934, and/or memory of theprocessor(s) 910 and/or the storage unit 936) may store one or more setsof instructions 916 and data structures (e.g., software) embodying orutilized by any one or more of the methodologies or functions describedherein. These instructions 916, when executed by the processor(s) 910,cause various operations to implement the disclosed embodiments.

As used herein, the terms “machine-storage medium,” “device-storagemedium,” and “computer-storage medium” mean the same thing and can beused interchangeably in this disclosure. The terms refer to a single ormultiple storage devices and/or media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storeexecutable instructions and/or data. The terms shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media, including memory internal or external toprocessors. Specific examples of machine-storage media, computer-storagemedia, and/or device-storage media include non-volatile memory,including by way of example semiconductor memory devices, e.g., erasableprogrammable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), field-programmable gate arrays(FPGAs), and flash memory devices; magnetic disks such as internal harddisks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The terms “machine-storage media,” “computer-storage media,” and“device-storage media” specifically exclude carrier waves, modulateddata signals, and other such media, at least some of which are coveredunder the term “signal medium” discussed below.

In various example embodiments, one or more portions of the network 981can be an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local-area network (LAN), a wireless LAN (WLAN), awide-area network (WAN), a wireless WAN (WWAN), a metropolitan-areanetwork (MAN), the Internet, a portion of the Internet, a portion of thepublic switched telephone network (PSTN), a plain old telephone service(POTS) network, a cellular telephone network, a wireless network, aWi-Fi® network, another type of network, or a combination of two or moresuch networks. For example, the network 981 or a portion of the network981 may include a wireless or cellular network, and the coupling 983 canbe a Code Division Multiple Access (CDMA) connection, a Global Systemfor Mobile communications (GSM) connection, or another type of cellularor wireless coupling. In this example, the coupling 983 may implementany of a variety of types of data transfer technology, such as SingleCarrier Radio Transmission Technology (1xRTT), Evolution-Data Optimized(EVDO) technology, General Packet Radio Service (GPRS) technology,Enhanced Data rates for GSM Evolution (EDGE) technology, thirdGeneration Partnership Project (3GPP) including 3G, fourth generationwireless (4G) networks, Universal Mobile Telecommunications System(UMTS), High-Speed Packet Access (HSPA), Worldwide Interoperability forMicrowave Access (WiMAX), Long Term Evolution (LTE) standard, othersdefined by various standard-setting organizations, other long-rangeprotocols, or other data transfer technology.

The instructions 916 can be transmitted or received over the network 981using a transmission medium via a network interface device (e.g., anetwork interface component included in the communication components964) and utilizing any one of a number of well-known transfer protocols(e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions916 can be transmitted or received using a transmission medium via thecoupling 982 (e.g., a peer-to-peer coupling) to the devices 980. Theterms “transmission medium” and “signal medium” mean the same thing andcan be used interchangeably in this disclosure. The terms “transmissionmedium” and “signal medium” shall be taken to include any intangiblemedium that is capable of storing, encoding, or carrying theinstructions 916 for execution by the machine 900, and include digitalor analog communications signals or other intangible media to facilitatecommunication of such software. Hence, the terms “transmission medium”and “signal medium” shall be taken to include any form of modulated datasignal, carrier wave, and so forth. The term “modulated data signal”means a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in the signal.

Described implementations of the subject matter can include one or morefeatures, alone or in combination as illustrated below by way ofexample.

Example 1 can include a method comprising: receiving, by at least onehardware processor, input data indicative of a selection of a link of aprimary database to share data from the primary database to a secondarydatabase, the primary database hosted in a multi-tenant deployment in adistributed database, the secondary database hosted in a privatedeployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.

In Example 2, the subject matter of Example 1 optionally includeswherein further comprising: detecting a modification to the data in theprimary database; updating the replicated data from the multi-tenantdeployment to the private deployment; and sharing the updated data fromthe secure share area to the secondary database.

In Example 3, the subject matter of any one of Examples 1-2 optionallyinclude wherein creating the secure share area in the private deploymentfurther comprises: generating metadata describing a set of data objectsincluded in the shared data.

In Example 4, the subject matter of any one of Examples 1-3 optionallyinclude wherein replicating the data from the multi-tenant deployment tothe private deployment further comprises: receiving confirmation thatthe data was successfully replicated; and notifying a user of thesecondary database hosted in the private deployment of the distributeddatabase of the confirmation.

In Example 5, the subject matter of any one of Examples 1-4 optionallyinclude wherein performing the one or more database operations on theshared data in the secondary database further comprises querying theshared data.

In Example 6, the subject matter of any one of Examples 1-5 optionallyinclude wherein receiving the input data indicative of the selection ofthe link of the primary database to share data from the primary databaseto the secondary database further comprises: receiving identifyinginformation related to the primary database to identify the primarydatabase hosted in the multi-tenant deployment as an authorizeddatabase, wherein the authorized database will not acquire direct accessto the private deployment.

In Example 7, the subject matter of any one of Examples 1-6 optionallyinclude wherein the link of the primary database includes a privatelisting offering shared data.

In Example 8, the subject matter of Example 7 optionally includeswherein replicating the data from the multi-tenant deployment to theprivate deployment further comprises: creating a replica share of thedata in the secure share area in the private deployment; and linking thereplica share to the private listing offering shared data.

In Example 9, the subject matter of any one of Examples 1-8 optionallyinclude wherein the shared data includes at least one of a data table, adata schema, a data view, a function, and a stored procedure.

Example 10 can include a system comprising: one or more hardwareprocessors of a machine; and at least one memory storing instructionsthat, when executed by the one or more hardware processors, cause themachine to perform operations comprising: receiving, by at least onehardware processor, input data indicative of a selection of a link of aprimary database to share data from the primary database to a secondarydatabase, the primary database hosted in a multi-tenant deployment in adistributed database, the secondary database hosted in a privatedeployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.

In Example 11, the subject matter of Example 10 optionally includeswherein the operations further comprising: detecting a modification tothe data in the primary database; updating the replicated data from themulti-tenant deployment to the private deployment; and sharing theupdated data from the secure share area to the secondary database.

In Example 12, the subject matter of any one of Examples 10-11optionally include optionally includes wherein creating the secure sharearea in the private deployment further comprises: generating metadatadescribing a set of data objects included in the shared data.

In Example 13, the subject matter of any one of Examples 10-12optionally include wherein replicating the data from the multi-tenantdeployment to the private deployment further comprises: receivingconfirmation that the data was successfully replicated; and notifying auser of the secondary database hosted in the private deployment of thedistributed database of the confirmation.

In Example 14, the subject matter of any one of Examples 10-13optionally include wherein performing the one or more databaseoperations on the shared data in the secondary database furthercomprises querying the shared data.

In Example 15, the subject matter of any one of Examples 10-14optionally include wherein receiving the input data indicative of theselection of the link of the primary database to share data from theprimary database to the secondary database further comprises: receivingidentifying information related to the primary database to identify theprimary database hosted in the multi-tenant deployment as an authorizeddatabase, wherein the authorized database will not acquire direct accessto the private deployment.

In Example 16, the subject matter of any one of Examples 10-15optionally include wherein the link of the primary database includes aprivate listing offering shared data.

In Example 17, the subject matter of Example 16 optionally includeswherein replicating the data from the multi-tenant deployment to theprivate deployment further comprises: creating a replica share of thedata in the secure share area in the private deployment; and linking thereplica share to the private listing offering shared data.

In Example 18, the subject matter of Example 17 optionally includeswherein the shared data includes at least one of a data table, a dataschema, a data view, a function, and a stored procedure.

Example 19 can include a machine-readable storage device embodyinginstructions that, when executed by a machine, cause the machine toperform operations comprising: receiving, by at least one hardwareprocessor, input data indicative of a selection of a link of a primarydatabase to share data from the primary database to a secondarydatabase, the primary database hosted in a multi-tenant deployment in adistributed database, the secondary database hosted in a privatedeployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.

In Example 20, the subject matter of Example 19 optionally includeswherein detecting a modification to the data in the primary database;updating the replicated data from the multi-tenant deployment to theprivate deployment; and sharing the updated data from the secure sharearea to the secondary database.

In Example 21, the subject matter of any one of Examples 19-20optionally include wherein creating the secure share area in the privatedeployment further comprises: generating metadata describing a set ofdata objects included in the shared data.

In Example 22, the subject matter of any one of Examples 19-21optionally include wherein replicating the data from the multi-tenantdeployment to the private deployment further comprises: receivingconfirmation that the data was successfully replicated; and notifying auser of the secondary database hosted in the private deployment of thedistributed database of the confirmation.

In Example 23, the subject matter of any one of Examples 19-22optionally include wherein performing the one or more databaseoperations on the shared data in the secondary database furthercomprises querying the shared data.

In Example 24, the subject matter of any one of Examples 19-23optionally include wherein receiving the input data indicative of theselection of the link of the primary database to share data from theprimary database to the secondary database further comprises: receivingidentifying information related to the primary database to identify theprimary database hosted in the multi-tenant deployment as an authorizeddatabase, wherein the authorized database will not acquire direct accessto the private deployment.

In Example 25, the subject matter of any one of Examples 19-24optionally include wherein the link of the primary database includes aprivate listing offering shared data.

In Example 26, the subject matter of Example 25 optionally includeswherein replicating the data from the multi-tenant deployment to theprivate deployment further comprises: creating a replica share of thedata in the secure share area in the private deployment; and linking thereplica share to the private listing offering shared data.

In Example 27, the subject matter of any one of Examples 19-26optionally include wherein the shared data includes at least one of adata table, a data schema, a data view, a function, and a storedprocedure.

The terms “machine-readable medium,” “computer-readable medium,” and“device-readable medium” mean the same thing and can be usedinterchangeably in this disclosure. The terms are defined to includeboth machine-storage media and transmission media. Thus, the termsinclude both storage devices/media and carrier waves/modulated datasignals.

The various operations of example methods described herein can beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Similarly, the methods described hereincan be at least partially processor implemented. For example, at leastsome of the operations of the methods described herein can be performedby one or more processors. The performance of certain of the operationscan be distributed among the one or more processors, not only residingwithin a single machine, but also deployed across a number of machines.In some example embodiments, the processor or processors can be locatedin a single location (e.g., within a home environment, an officeenvironment, or a server farm), while in other embodiments theprocessors can be distributed across a number of locations.

Although the embodiments of the present disclosure have been describedwith reference to specific example embodiments, it will be evident thatvarious modifications and changes can be made to these embodimentswithout departing from the broader scope of the inventive subjectmatter. Accordingly, the specification and drawings are to be regardedin an illustrative rather than a restrictive sense. The accompanyingdrawings that form a part hereof show, by way of illustration, and notof limitation, specific embodiments in which the subject matter can bepracticed. The embodiments illustrated are described in sufficientdetail to enable those skilled in the art to practice the teachingsdisclosed herein. Other embodiments can be used and derived therefrom,such that structural and logical substitutions and changes can be madewithout departing from the scope of this disclosure. This DetailedDescription, therefore, is not to be taken in a limiting sense, and thescope of various embodiments is defined only by the appended claims,along with the full range of equivalents to which such claims areentitled.

Such embodiments of the inventive subject matter can be referred toherein, individually and/or collectively, by the term “invention” merelyfor convenience and without intending to voluntarily limit the scope ofthis application to any single invention or inventive concept if morethan one is in fact disclosed. Thus, although specific embodiments havebeen illustrated and described herein, it should be appreciated that anyarrangement calculated to achieve the same purpose can be substitutedfor the specific embodiments shown. This disclosure is intended to coverany and all adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart, upon reviewing the above description.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In the appended claims, the terms “including” and“in which” are used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended; that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim is still deemed to fall within thescope of that claim.

What is claimed is:
 1. A method comprising: receiving, by at least onehardware processor, input data indicative of a selection of a link of aprimary database to share data from the primary database to a secondarydatabase, the primary database hosted in a multi-tenant deployment in adistributed database, the secondary database hosted in a privatedeployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.
 2. The methodof claim 1, further comprising: detecting a modification to the data inthe primary database; updating the replicated data from the multi-tenantdeployment to the private deployment; and sharing the updated data fromthe secure share area to the secondary database.
 3. The method of claim1, wherein creating the secure share area in the private deploymentfurther comprises: generating metadata describing a set of data objectsincluded in the shared data.
 4. The method of claim 1, whereinreplicating the data from the multi-tenant deployment to the privatedeployment further comprises: receiving confirmation that the data wassuccessfully replicated; and notifying a user of the secondary databasehosted in the private deployment of the distributed database of theconfirmation.
 5. The method of claim 1, wherein performing the one ormore database operations on the shared data in the secondary databasefurther comprises querying the shared data.
 6. The method of claim 1,wherein receiving the input data indicative of the selection of the linkof the primary database to share data from the primary database to thesecondary database further comprises: receiving identifying informationrelated to the primary database to identify the primary database hostedin the multi-tenant deployment as an authorized database, wherein theauthorized database will not acquire direct access to the privatedeployment.
 7. The method of claim 1, wherein the link of the primarydatabase includes a private listing offering shared data.
 8. The methodof claim 7, wherein replicating the data from the multi-tenantdeployment to the private deployment further comprises: creating areplica share of the data in the secure share area in the privatedeployment; and linking the replica share to the private listingoffering shared data.
 9. The method of claim 1, wherein the shared dataincludes at least one of a data table, a data schema, a data view, afunction, and a stored procedure.
 10. A system comprising: one or morehardware processors of a machine; and at least one memory storinginstructions that, when executed by the one or more hardware processors,cause the machine to perform operations comprising: receiving, by atleast one hardware processor, input data indicative of a selection of alink of a primary database to share data from the primary database to asecondary database, the primary database hosted in a multi-tenantdeployment in a distributed database, the secondary database hosted in aprivate deployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.
 11. The systemof claim 10, the operations further comprising: detecting a modificationto the data in the primary database; updating the replicated data fromthe multi-tenant deployment to the private deployment; and sharing theupdated data from the secure share area to the secondary database. 12.The system of claim 10, wherein creating the secure share area in theprivate deployment further comprises: generating metadata describing aset of data objects included in the shared data.
 13. The system of claim10, wherein replicating the data from the multi-tenant deployment to theprivate deployment further comprises: receiving confirmation that thedata was successfully replicated; and notifying a user of the secondarydatabase hosted in the private deployment of the distributed database ofthe confirmation.
 14. The system of claim 10, wherein performing the oneor more database operations on the shared data in the secondary databasefurther comprises querying the shared data.
 15. The system of claim 10,wherein receiving the input data indicative of the selection of the linkof the primary database to share data from the primary database to thesecondary database further comprises: receiving identifying informationrelated to the primary database to identify the primary database hostedin the multi-tenant deployment as an authorized database, wherein theauthorized database will not acquire direct access to the privatedeployment.
 16. The system of claim 10, wherein the link of the primarydatabase includes a private listing offering shared data.
 17. The systemof claim 16, wherein replicating the data from the multi-tenantdeployment to the private deployment further comprises: creating areplica share of the data in the secure share area in the privatedeployment; and linking the replica share to the private listingoffering shared data.
 18. The system of claim 17, wherein the shareddata includes at least one of a data table, a data schema, a data view,a function, and a stored procedure.
 19. A machine-readable storagedevice embodying instructions that, when executed by a machine, causethe machine to perform operations comprising: receiving, by at least onehardware processor, input data indicative of a selection of a link of aprimary database to share data from the primary database to a secondarydatabase, the primary database hosted in a multi-tenant deployment in adistributed database, the secondary database hosted in a privatedeployment of the distributed database; in response to the link,creating a secure share area in the private deployment; replicating thedata from the multi-tenant deployment to the private deployment;sharing, in the private deployment, the data from the secure share areato the secondary database; and performing one or more databaseoperations on the shared data in the secondary database.
 20. Themachine-readable storage device of claim 19, wherein detecting amodification to the data in the primary database; updating thereplicated data from the multi-tenant deployment to the privatedeployment; and sharing the updated data from the secure share area tothe secondary database.
 21. The machine-readable storage device of claim19, wherein creating the secure share area in the private deploymentfurther comprises: generating metadata describing a set of data objectsincluded in the shared data.
 22. The machine-readable storage device ofclaim 19, wherein replicating the data from the multi-tenant deploymentto the private deployment further comprises: receiving confirmation thatthe data was successfully replicated; and notifying a user of thesecondary database hosted in the private deployment of the distributeddatabase of the confirmation.
 23. The machine-readable storage device ofclaim 19, wherein performing the one or more database operations on theshared data in the secondary database further comprises querying theshared data.
 24. The machine-readable storage device of claim 19,wherein receiving the input data indicative of the selection of the linkof the primary database to share data from the primary database to thesecondary database further comprises: receiving identifying informationrelated to the primary database to identify the primary database hostedin the multi-tenant deployment as an authorized database, wherein theauthorized database will not acquire direct access to the privatedeployment.
 25. The machine-readable storage device of claim 19, whereinthe link of the primary database includes a private listing offeringshared data.
 26. The machine-readable storage device of claim 25,wherein replicating the data from the multi-tenant deployment to theprivate deployment further comprises: creating a replica share of thedata in the secure share area in the private deployment; and linking thereplica share to the private listing offering shared data.
 27. Themachine-readable storage device of claim 19, wherein the shared dataincludes at least one of a data table, a data schema, a data view, afunction, and a stored procedure.